Cloud-Assisted IoT-Enabled Smoke Monitoring System (e-Nose) Using Machine Learning Techniques

  • Somya GoyalEmail author
  • Pradeep K. Bhatia
  • Anubha Parashar
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 141)


E-nose is a self-controlled smoke detector developed using Arduino microcontroller and sensors. It is capable of sensing the smell in the ambiance via gas sensors and programmed to alert the smokers giving red signal with buzzer. Smoke detection algorithm facilitates the intelligent warning to the cigarette smokers. Nowadays, smokers’ count is increasing with a high-speed raising health and moral issues to the people especially in case of passive smoking at public places. Today “No Smoking” rules are only written, but to make these rules being followed this work would be a milestone. To implement e-Nose, a cigarette smoke detector with red/green LED and buzzer using Arduino uno board R3 is developed. MQ-2 gas sensor is used to detect cigarette smoke and combination of buzzer and LEDs is used to warn smokers. This work demonstrates the development of e-Nose and evaluation of the performance of developed product. In nutshell, this e-Nose which is cigarette smoke detector is designed to achieve high degree of awareness among public and to reduce the smokers’ count especially at public places. We detect the smoke through e-Nose and upload on the cloud. The cloud analysis is done using various machine learning techniques to categorize the smoke with pollution data. And result shows smoking percentage.


Mobile robot Gas sensor Arduino Smoke detection Microcontroller Buzzer LED 


  1. 1.
    Institute for Public Health (IPH): Report of the Global Adult Tobacco Survey (GATS) Malaysia, 2011, Ministry of Health Malaysia (2012)Google Scholar
  2. 2.
    Svendsen, K.H., Kuller, L.H., Martin, M.J., Ockene, J.K.: Effects of passive smoking in the multiple risk factor intervention trial. Am. J. Epidemiol. 126(5), 783–795 (1987)Google Scholar
  3. 3.
    Barnoya, J., Glantz, S.A.: Cardiovascular effects of secondhand smoke nearly as large as smoking. Circulation 111, 2684–2698 (2005).
  4. 4.
    Phillips, D.H., Schoket, B., Hewer, A., Bailey, E., Kostic, S., Vincze, I.: Influence of cigarette smoking on the levels of DNA adducts in human bronchial epithelium and white blood cells. Int. J. Cancer 46(4), 569–575 (1990)Google Scholar
  5. 5.
    Celik, T., Demirel, H., Ozkaramanli, H., Uyguroglu, M.: Fire detection using statistical color model in video sequences. J. Vis. Commun. Image Represent. 18(2), 176–185 (2007)CrossRefGoogle Scholar
  6. 6.
    Dedeoglu, N., Toreyin, B.U., Gudukbay, U., Cetin, A.E.: Real-time fire and flame detection in video. In: ICASSP, vol. 2, pp. 669–672 (2005)Google Scholar
  7. 7.
    Krstinic, D., Stipanicev, D., Jakovcevi´c, T.: Histogram based smoke segmentation in forest fire detection system. Inf. Technol. Control. 38(3) (2015)Google Scholar
  8. 8.
    Liu, C.B., Ahuja, N.: Vision based fire detection. In: Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004, vol. 4. pp. 134–137. IEEE (2004)Google Scholar
  9. 9.
    Toreyin, B.U., Dedeoglu, Y., Cetin, A.E.: Wavelet based real-time smoke detection in video. In: Proceedings of IEEE Conference (13th European) Signal Processing, pp. 1–4 (2005)Google Scholar
  10. 10.
    Bahrepour, M., Meratnia, N., Havinga, P.J.: Automatic fire detection: a survey from wireless sensor network perspective (2008)Google Scholar
  11. 11.
    Yu, L., Wang, N., Meng, X.: Real-time forest fire detection with wireless sensor networks. In: Wireless Communications, Networking and Mobile Computing. Proceedings. 2005 International Conference on, IEEE, vol. 2, pp. 1214–1217 (2005)Google Scholar
  12. 12.
    Goyal, S., Parashar, A.: Machine learning application to improve COCOMO Model using neural networks. Int. J. Inf. Technol. Comput. Sci. (IJITCS). 10(3), 35–51 (2018).

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Somya Goyal
    • 1
    Email author
  • Pradeep K. Bhatia
    • 1
  • Anubha Parashar
    • 2
  1. 1.GJUS & THisarIndia
  2. 2.Manipal UniversityJaipurIndia

Personalised recommendations